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  • This directory contains volcanic SO2 data derived from limb viewing satellites for the lower stratosphere from 1990 to 2019. The usage of the data is described in Timmreck et al., (2018), datasets VolcDB1 and VolcDB1_3D. We provide 3D-plumes of observed volume mixing ratio perturbations in the lower stratosphere / upper troposphere typically derived from 10-day periods as nc-file and integrated values of injected SO2 mass with peak latitudes and altitudes as Fortran formatted ascii file (33X,A11,5X,6(I3,1X),I4,1X,5(I3,1X),6(I3,1X),I5,1X,4(I3,1X),I3) for at maximum 6 events at one time. Instead of A11 I2,A4,I5 can be used to read in the components of time. The data from Jan. 1990 to Jan. 2002 are based on L2-files of SAGE II (V7.0) provided by the NASA DAAC (Thomason et al., 2008). The data from Jul. 2002 to Mar. 2012 use the updated 5-day time series of MIPAS (Hoepfner et al., 2015), supplemented by SO2 derived from GOMOS extinctions (Bingen et al., 2017, with a corresponding table, scaled for lower resolution). After March 2012 based on OSIRIS (Rieger et al., 2019). volc_SO2-3D-vmr-perturbation-1990-2019.nc: 3D SO2 for 258 days with eruptions in T63L90 resolution (ECHAM-grid in grid-T63L90.nc). Latitude from South to North, for use with ECHAM please reverse. The levels on the hybrid-grid in the grid files are defined as lev(x,y,z)=hyam(z)+hybm(z)*apsave(x,y), in Pa (apsave annual average of surface pressure or orography), surface to 80km (update of VolcDB1_3D). This version contains the factors of Brühl et al. (2018) for MIPAS included in the ascii-file with the integrals and which were missing in Version 2 (SSIRC_2). volc-so2-inventory.ps: plot of zonal averages of SO2 perturbation at 3 altitudes (gaps not shown, widths of bars have no meaning). volc-SO2-mass.txt: integrated SO2 mass injected (in kt), SAGE, ENVISAT and OSIRIS period (update of VolcDB1). The volcano names are in the first column, see also http://www.volcano.si.edu (Smithsonian volcano database), Schallock et al. (2021) and SSIRC_1 (doi:10.1594/WDCC/SSIRC_1). AEROCOM-DIEHL-degassing-volc-SO2.nc: Fluxes from outgassing volcanoes in the troposphere (below 210hPa), taken from AEROCOM (Diehl et al., 2012). Caution, filled with odd climatology after 2009, monthly (subset beginning Jan. 1990). volc-globalforcing-tropo.nc: EMAC results for instanteneous global radiative radiative forcing by stratospheric aerosol near the tropopause (in W/m2), figure see Schallock et al. (2021)

  • preindustrial Control experiment to be used in VolMIP analyses. The piControl experiment is the CMIP6-DECK piControl experiment described in Eyring et al. (2016). piControl provides initial climate states that are sampled to start most of VolMIP experiments (Zanchettin et al., 2016). The dataset contains monthly values of selected variables spatially averaged over four regions. These are the full globe (GL), the Northern Hemisphere extratropics (30°-90°N, NH), the tropics (30°S-30°N, TR), and the Southern Hemisphere (30°-90°S, hereafter SH). The considered variables have the following cmor names: hfls, hfss, pr, rlds, rldscs, rlus, rlut, rlutcs, rsds, rsdscs, rsdt, rsus, rsut, rsutcs, tas. Additionally, the climate indices NAO and Nino34 are part of the dataset. Considered models are CanESM5, IPSL-CM6A-LR, GISS-E2.1-G, MIROC-ES2L, MPI-ESM1.2-LR (named MPI-ESM-LR in the files of this dataset) and UKESM1. Considered experiments are piControl and volc-pinatubo-full, with initial date and final date as specified for each model in Zanchettin et al. (2021). Different realizations are considered for the participating models depending on availability.

  • WebMapService for climate data hosted by Deutscher Wetterdienst

  • postprocessed (downscaled an bias corrected) daily means of 2-meter-air-temperature, global radiation and daily amount of precipitation; based on regional climate projections; focussed on the period 1951-2100; gridded with 5 km horizontal spatial resolution; refers to Germany and hydrological catchment areas of Danube, Rhine, Elbe and Odra; was founded by KLIWAS (Impacts of climate change on Waterways and Navigation); provided by Department Climate and Environment Consultancy of Deutscher Wetterdienst

  • Quarterly collections of none-real-time data from marine stations, e.g. ships, buoys, platforms together with the metadata and quality control information, which were rejected during minimum quality control

  • While climate information from General Circulation Models (GCMs) are usually too coarse for climate impact modelers or decision makers from various disciplines (e.g., hydrology, agriculture), Regional Climate Models (RCMs) and Regional Earth System Models (RESMs) provide feasible solutions for downscaling GCM output to finer spatiotemporal scales. However, it is well known that the model performance depends largely on the choice of the physical parameterization schemes, but optimal configurations may vary from region to region. Besides land-surface processes, the most crucial processes to be parameterized in ESMs include radiation (RA), cumulus convection (CU), cloud microphysics (MP), and planetary boundary layer (PBL), partly with complex interactions. Before conducting long-term climate simulations, it is therefore indispensable to identify a suitable combination of physics parameterization schemes for these processes. Using the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis product ERA-Interim as lateral boundary conditions, we derived an ensemble of 16 physics parameterization runs for a larger domain in Northern sub-Saharan Africa (NSSA), northwards of the equator, using two different CU-, MP-, PBL-, and RA schemes, respectively, using the Weather Research and Forecasting (WRF) model (Version v3.9) for the period 2006-2010 in a resolution of 0.1 degree horizontal resolution. Conclusions about suitable physical parameterization schemes may vary within the study area. We therefore want to stimulate the development of own performance evaluation studies for climate simulations or subsequent impact studies over specific (sub-)regions in NSSA. For this reason, selected climate surface variables of the physics ensemble (i.e. the 16 experiments from 2006-2010) are provided. For more information about the setup of the experiments, please see: Laux et al., 2021: A high-resolution regional climate model physics ensemble for Northern sub-Saharan Africa. Frontiers in Earth Science (under revision).

  • While climate information from General Circulation Models (GCMs) are usually too coarse for climate impact modelers or decision makers from various disciplines (e.g., hydrology, agriculture), Regional Climate Models (RCMs) and Regional Earth System Models (RESMs) provide feasible solutions for downscaling GCM output to finer spatiotemporal scales. However, it is well known that the model performance depends largely on the choice of the physical parameterization schemes, but optimal configurations may vary from region to region. Besides land-surface processes, the most crucial processes to be parameterized in ESMs include radiation (RA), cumulus convection (CU), cloud microphysics (MP), and planetary boundary layer (PBL), partly with complex interactions. Before conducting long-term climate simulations, it is therefore indispensable to identify a suitable combination of physics parameterization schemes for these processes. Using the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis product ERA-Interim as lateral boundary conditions, we derived an ensemble of 16 physics parameterization runs for a larger domain in Northern sub-Saharan Africa (NSSA), northwards of the equator, using two different CU-, MP-, PBL-, and RA schemes, respectively, using the Weather Research and Forecasting (WRF) model (Version v3.9) for the period 2006-2010 in a resolution of 0.1 degree horizontal resolution. Conclusions about suitable physical parameterization schemes may vary within the study area. We therefore want to stimulate the development of own performance evaluation studies for climate simulations or subsequent impact studies over specific (sub-)regions in NSSA. For this reason, selected climate surface variables of the physics ensemble (i.e. the 16 experiments from 2006-2010) are provided. For more information about the setup of the experiments, please see: Laux et al., 2021: A high-resolution regional climate model physics ensemble for Northern sub-Saharan Africa. Frontiers in Earth Science (under revision).

  • While climate information from General Circulation Models (GCMs) are usually too coarse for climate impact modelers or decision makers from various disciplines (e.g., hydrology, agriculture), Regional Climate Models (RCMs) and Regional Earth System Models (RESMs) provide feasible solutions for downscaling GCM output to finer spatiotemporal scales. However, it is well known that the model performance depends largely on the choice of the physical parameterization schemes, but optimal configurations may vary from region to region. Besides land-surface processes, the most crucial processes to be parameterized in ESMs include radiation (RA), cumulus convection (CU), cloud microphysics (MP), and planetary boundary layer (PBL), partly with complex interactions. Before conducting long-term climate simulations, it is therefore indispensable to identify a suitable combination of physics parameterization schemes for these processes. Using the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis product ERA-Interim as lateral boundary conditions, we derived an ensemble of 16 physics parameterization runs for a larger domain in Northern sub-Saharan Africa (NSSA), northwards of the equator, using two different CU-, MP-, PBL-, and RA schemes, respectively, using the Weather Research and Forecasting (WRF) model (Version v3.9) for the period 2006-2010 in a resolution of 0.1 degree horizontal resolution. Conclusions about suitable physical parameterization schemes may vary within the study area. We therefore want to stimulate the development of own performance evaluation studies for climate simulations or subsequent impact studies over specific (sub-)regions in NSSA. For this reason, selected climate surface variables of the physics ensemble (i.e. the 16 experiments from 2006-2010) are provided. For more information about the setup of the experiments, please see: Laux et al., 2021: A high-resolution regional climate model physics ensemble for Northern sub-Saharan Africa. Frontiers in Earth Science (under revision).

  • The data contains the emission variation simulations which build the lookup-tables for TransClim. Eleven emission regions are defined: Germany, Western Europe, Northern Europe, Eastern Europe, Southern Europe, China, India, Southeast Asia, Japan/South Korea, North America and South America. In each of these emission regions, the road traffic emissions of nitrogen oxide (NOx), volatile organic compounds (VOC) and carbon monooxide (CO) are varied and the resulting climate response is calculated with the global chemistry climate model EMAC.

  • The data of this experiment have been used in (Hagemann et al., 2020). It comprise daily data of surface runoff and subsurface runoff (drainage) from JSBACH and MPI-HM and simulated daily discharges (river runoff). To generate river runoff, the Hydrological discharge (HD) model (Hagemann et al., 2020; Hagemann and Ho-Hagemann, 2021) was used that was operated at 5 arc minutes horizontal resolution. Different to the published version of HD model parameters (5.0) on Zenodo, an earlier version (4.0) of flow directions and model parameters has been used that is provided as an auxiliary data file. The HD model was set up over the European domain covering the land areas between -11°W to 69°E and 27°N to 72°N. First, the respective forcing data of surface and sub-surface runoff were interpolated to the HD model domain using conservative remapping. Then, daily discharges were simulated with the HD model for the period 1979-2009 (1999-2009 for HD5-MESCAN). In addition, daily discharges were analogously simulated using only JSBACH forcing with the global 0.5° version 1.10 of the HD model. The associated flow directions and model parameters of vs. 1.10 are provided as an auxiliary data file. The HD forcing data are: a) HD5-JSBACH In order to generate daily input fields of surface runoff and drainage, the land surface scheme JSBACH (vs. 3 + frozen soil physics; (Ekici et al., 2014)) was forced globally at 0.5° with daily atmospheric forcing data based on the Interim Re-Analysis of the European Centre for Medium-Range Weather Forecast (ERA-Interim; (Dee et al., 2011)). These forcing data are bias-corrected (see (Beer et al., 2014)) towards the so-called WATCH forcing data (WFD; (Weedon et al., 2011)) that have been generated in the EU project WATCH. b) HD5-MPIHM The MPI-M hydrology model MPI-HM (Stacke and Hagemann, 2012) was driven by daily WATCH forcing data based on ERA-Interim (WFDEI; (Weedon et al., 2014)) from 1979-2009 to generate daily input fields of surface runoff and drainage at global 0.5° resolution. c) HD5-MESCAN Six hourly data of surface runoff and drainage (variable name: percolation) were retrieved from the MESCAN-SURFEX regional surface reanalysis (Bazile et al., 2017) created in the EU project UERRA (Uncertainties in Ensembles of Regional ReAnalysis; www.uerra.eu). SURFEX (Masson et al., 2013) is a land surface platform that was driven by atmospheric forcing at 5.5 km. The forcing comprises 24h-precipitation, near-surface temperature and relative humidity analyzed by the MESCAN surface analysis system as well as radiative fluxes and wind downscaled at 5.5 km from the 3DVar re-analysis conducted with the HARMONIE system at 11 km (Ridal et al., 2017). The latter has been generated using six-hourly fields of the ERA-Interim reanalysis as boundary conditions and covers a domain comprising Europe and parts of the Atlantic, which is similar to the European domain of the Coordinated Downscaling Experiment (CORDEX) at 11 km.

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